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. 2020 Oct 2;370(6512):89-94.
doi: 10.1126/science.abd3871. Epub 2020 Aug 4.

Selective and cross-reactive SARS-CoV-2 T cell epitopes in unexposed humans

Jose Mateus  1 , Alba Grifoni  1 , Alison Tarke  1 , John Sidney  1 , Sydney I Ramirez  1   2 , Jennifer M Dan  1   2 , Zoe C Burger  2 , Stephen A Rawlings  2 , Davey M Smith  2 , Elizabeth Phillips  3 , Simon Mallal  3 , Marshall Lammers  1 , Paul Rubiro  1 , Lorenzo Quiambao  1 , Aaron Sutherland  1 , Esther Dawen Yu  1 , Ricardo da Silva Antunes  1 , Jason Greenbaum  1 , April Frazier  1 , Alena J Markmann  4 , Lakshmanane Premkumar  5 , Aravinda de Silva  5 , Bjoern Peters  1   2 , Shane Crotty  1   2 , Alessandro Sette #  6   2 , Daniela Weiskopf #  6
Affiliations

Selective and cross-reactive SARS-CoV-2 T cell epitopes in unexposed humans

Jose Mateus et al. Science. .

Abstract

Many unknowns exist about human immune responses to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. SARS-CoV-2-reactive CD4+ T cells have been reported in unexposed individuals, suggesting preexisting cross-reactive T cell memory in 20 to 50% of people. However, the source of those T cells has been speculative. Using human blood samples derived before the SARS-CoV-2 virus was discovered in 2019, we mapped 142 T cell epitopes across the SARS-CoV-2 genome to facilitate precise interrogation of the SARS-CoV-2-specific CD4+ T cell repertoire. We demonstrate a range of preexisting memory CD4+ T cells that are cross-reactive with comparable affinity to SARS-CoV-2 and the common cold coronaviruses human coronavirus (HCoV)-OC43, HCoV-229E, HCoV-NL63, and HCoV-HKU1. Thus, variegated T cell memory to coronaviruses that cause the common cold may underlie at least some of the extensive heterogeneity observed in coronavirus disease 2019 (COVID-19) disease.

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Figures

Fig. 1
Fig. 1. Characteristics of SARS-CoV-2 epitopes identified in unexposed donors.
Reactivity was determined by FluoroSPOT assay after 17 days of in vitro stimulation of unexposed donor PBMCs (n = 18) with one pool of peptides spanning the entire sequence of the spike protein (CD4-S) or a nonspike “megapool” (CD4-R) of predicted epitopes from the nonspike (i.e., “remainder”) regions of the viral genome. (A) Summary of the responses as a function of the protein of origin. (B) Spearman correlation of positive responses per SARS-CoV-2 protein size. (C) Percent similarity of the identified epitopes with common cold coronavirus peptides as a function of the number of responding donors. (D) Each dot shows the reactivity of a donor-epitope combination derived from either nonspike (CD4-R) or spike (CD4-S) protein. Black bars indicate the geometric mean and geometric SD. Red indicates donor-epitope combinations with sequence identity >67% with common cold coronaviruses, and blue indicates highly reactive donor-epitope combinations (>1000 SFCs*106) with sequence identity ≤67%. In (C) and (D), statistical comparisons were performed with a two-tailed Mann–Whitney test. ***P < 0.001, ****P < 0.0001.
Fig. 2
Fig. 2. CD4+ T cells in SARS-CoV-2–unexposed and recovered COVID-19 patients against HCoV epitopes homologous to SARS-CoV-2 epitopes.
(A) Example of flow cytometry gating strategy for antigen-specific CD4+ T cells based on activation-induced marker assays (OX40+ and CD137+ double expression) after stimulation of PBMCs with HCoV or SARS-CoV-2 peptides. (B to D) Antigen-specific CD4+ T cells measured as the percentage of activation-induced marker assay–positive (OX40+CD137+) CD4+ T cells after stimulation of PBMCs with HCoV epitopes homologous to SARS-CoV-2 epitopes. Samples were derived from SARS-CoV-2–unexposed donors (n = 25) and recovered COVID-19 patients ( n = 20). Black bars indicate the geometric mean and geometric SD. Each dot is representative of an individual subject. Statistical pairwise comparisons [(B) and (C)] were performed with the Wilcoxon test. P values related to comparisons with the DMSO controls are listed at the bottom of the graphs, and any significant P values related to intergroup comparisons are listed on top of the graphs. Statistical comparisons across cohorts were performed with the Mann–Whitney test (D). See also figs. S5 and S6.
Fig. 3
Fig. 3. Phenotypes of antigen-specific CD4+ T cells from SARS-CoV-2–unexposed and recovered COVID-19 patients responding to HCoV epitopes homologous to SARS-CoV-2 epitopes.
(A) Example of flow cytometry gating strategy for antigen-specific CD4+ T cell subsets after overnight stimulation of PBMCs with HCoV or SARS-CoV-2 peptides ex vivo. (B and C) Phenotype of antigen-specific CD4+ T cells (OX40+CD137+) responding to the indicated pools of SARS-CoV-2 and HCoV epitopes in unexposed subjects and recovered COVID-19 patients. Data are shown as mean ± SD. Each dot represents an individual subject. Statistical pairwise comparisons in (B) and (C) were performed with the Wilcoxon test. (D) Overall averages of antigen-specific CD4+ T cell subsets detected in unexposed subjects and recovered COVID-19 patients. See also fig. S5.
Fig. 4
Fig. 4. Cross-reactivity of SARS-CoV-2 and homologous HCoV peptides.
Twelve short-term cell lines were generated using specific SARS-CoV-2 donor-epitope combinations selected on the basis of the primary screen. After 14 days of in vitro expansion, each T cell line was tested with the SARS-CoV-2 epitope used for stimulation and peptides corresponding to analogous sequences from other HCoVs at six different concentrations (1, 0.1, 0.01, 0.001, 0.0001, and 0.00001 μg/ml). SFCs/106 PBMCs are plotted for T cell lines stimulated with each peptide. See also fig. S7.
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